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      Incidence and prevalence of tuberculosis in incarcerated populations: a systematic review and meta-analysis

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          Summary

          Background

          Prisons are recognised as high-risk environments for tuberculosis, but there has been little systematic investigation of the global and regional incidence and prevalence of tuberculosis, and its determinants, in prisons. We did a systematic review and meta-analysis to assess the incidence and prevalence of tuberculosis in incarcerated populations by geographical region.

          Methods

          In this systematic review and meta-analysis, we searched MEDLINE, Embase, Web of Knowledge, and the LILACS electronic database from Jan 1, 1980, to Nov 15, 2020, for cross-sectional and cohort studies reporting the incidence of Mycobacterium tuberculosis infection, incidence of tuberculosis, or prevalence of tuberculosis among incarcerated individuals in all geographical regions. We extracted data from individual studies, and calculated pooled estimates of incidence and prevalence through hierarchical Bayesian meta-regression modelling. We also did subgroup analyses by region. Incidence rate ratios between prisons and the general population were calculated by dividing the incidence of tuberculosis in prisons by WHO estimates of the national population-level incidence.

          Findings

          We identified 159 relevant studies; 11 investigated the incidence of M tuberculosis infection (n=16 318), 51 investigated the incidence of tuberculosis (n=1 858 323), and 106 investigated the prevalence of tuberculosis (n=6 727 513) in incarcerated populations. The overall pooled incidence of M tuberculosis infection among prisoners was 15·0 (95% credible interval [CrI] 3·8–41·6) per 100 person-years. The incidence of tuberculosis (per 100 000 person-years) among prisoners was highest in studies from the WHO African (2190 [95% CrI 810–4840] cases) and South-East Asia (1550 [240–5300] cases) regions and in South America (970 [460–1860] cases), and lowest in North America (30 [20–50] cases) and the WHO Eastern Mediterranean region (270 [50–880] cases). The prevalence of tuberculosis was greater than 1000 per 100 000 prisoners in all global regions except for North America and the Western Pacific, and highest in the WHO South-East Asia region (1810 [95% CrI 670–4000] cases per 100 000 prisoners). The incidence rate ratio between prisons and the general population was much higher in South America (26·9; 95% CrI 17·1–40·1) than in other regions, but was nevertheless higher than ten in the WHO African (12·6; 6·2–22·3), Eastern Mediterranean (15·6; 6·5–32·5), and South-East Asia (11·7; 4·1–27·1) regions.

          Interpretation

          Globally, people in prison are at high risk of contracting M tuberculosis infection and developing tuberculosis, with consistent disparities between prisons and the general population across regions. Tuberculosis control programmes should prioritise preventive interventions among incarcerated populations.

          Funding

          US National Institutes of Health.

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          Most cited references39

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          Quantifying heterogeneity in a meta-analysis.

          The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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            Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data: the PRISMA-IPD Statement.

            Systematic reviews and meta-analyses of individual participant data (IPD) aim to collect, check, and reanalyze individual-level data from all studies addressing a particular research question and are therefore considered a gold standard approach to evidence synthesis. They are likely to be used with increasing frequency as current initiatives to share clinical trial data gain momentum and may be particularly important in reviewing controversial therapeutic areas. To develop PRISMA-IPD as a stand-alone extension to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement, tailored to the specific requirements of reporting systematic reviews and meta-analyses of IPD. Although developed primarily for reviews of randomized trials, many items will apply in other contexts, including reviews of diagnosis and prognosis. Development of PRISMA-IPD followed the EQUATOR Network framework guidance and used the existing standard PRISMA Statement as a starting point to draft additional relevant material. A web-based survey informed discussion at an international workshop that included researchers, clinicians, methodologists experienced in conducting systematic reviews and meta-analyses of IPD, and journal editors. The statement was drafted and iterative refinements were made by the project, advisory, and development groups. The PRISMA-IPD Development Group reached agreement on the PRISMA-IPD checklist and flow diagram by consensus. Compared with standard PRISMA, the PRISMA-IPD checklist includes 3 new items that address (1) methods of checking the integrity of the IPD (such as pattern of randomization, data consistency, baseline imbalance, and missing data), (2) reporting any important issues that emerge, and (3) exploring variation (such as whether certain types of individual benefit more from the intervention than others). A further additional item was created by reorganization of standard PRISMA items relating to interpreting results. Wording was modified in 23 items to reflect the IPD approach. PRISMA-IPD provides guidelines for reporting systematic reviews and meta-analyses of IPD.
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              Global burden of HIV, viral hepatitis, and tuberculosis in prisoners and detainees.

              The prison setting presents not only challenges, but also opportunities, for the prevention and treatment of HIV, viral hepatitis, and tuberculosis. We did a comprehensive literature search of data published between 2005 and 2015 to understand the global epidemiology of HIV, hepatitis C virus (HCV), hepatitis B virus (HBV), and tuberculosis in prisoners. We further modelled the contribution of imprisonment and the potential impact of prevention interventions on HIV transmission in this population. Of the estimated 10·2 million people incarcerated worldwide on any given day in 2014, we estimated that 3·8% have HIV (389 000 living with HIV), 15·1% have HCV (1 546 500), 4·8% have chronic HBV (491 500), and 2·8% have active tuberculosis (286 000). The few studies on incidence suggest that intraprison transmission is generally low, except for large-scale outbreaks. Our model indicates that decreasing the incarceration rate in people who inject drugs and providing opioid agonist therapy could reduce the burden of HIV in this population. The prevalence of HIV, HCV, HBV, and tuberculosis is higher in prison populations than in the general population, mainly because of the criminalisation of drug use and the detention of people who use drugs. The most effective way of controlling these infections in prisoners and the broader community is to reduce the incarceration of people who inject drugs.
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                Author and article information

                Contributors
                Journal
                101699003
                46113
                Lancet Public Health
                Lancet Public Health
                The Lancet. Public health
                2468-2667
                15 May 2021
                22 March 2021
                May 2021
                01 June 2021
                : 6
                : 5
                : e300-e308
                Affiliations
                Division of Infectious Diseases and Geographic Medicine, Stanford, CA, USA
                Division of Infectious Diseases and Geographic Medicine, Stanford, CA, USA; Department of Epidemiology, School of Public Health, Boston University, Boston, MA, USA
                Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
                Division of Infectious Diseases and Geographic Medicine, Stanford, CA, USA; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
                Division of Infectious Diseases and Geographic Medicine, Stanford, CA, USA
                Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
                Stanford University School of Medicine, Stanford, CA, USA
                Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA; Oswaldo Cruz Foundation, Salvador, Brazil
                Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA; Universidade Federal de Mato Grosso do Sul, Faculdade de Medicina, Campo Grande, Mato Grosso do Sul, Brazil; Fundação Oswaldo Cruz, Campo Grande, Mato Grosso do Sul, Brazil
                Division of Infectious Diseases and Geographic Medicine, Stanford, CA, USA
                Author notes
                Correspondence to: Dr Leonardo Martinez, Department of Epidemiology, School of Public Health, Boston University, Boston, MA 02118, USA, leomarti@ 123456bu.edu
                [*]

                Joint first authors

                Contributors

                LM, OC, and JRA conceived the study. LM and OC did the systematic search. LM and OC screened and identified eligible studies. LM and OC made final decisions about inclusion of articles. LM, OC, JMO, and JZ extracted data from eligible studies. LM, OC, and KSW extracted data from studies in languages other than English. LM, OC, JLW, TC, and JRA designed the analyses. OC and LM received and checked the data. OC, LM, JLW, and JRA did the analyses and had full access to all materials and results. LM, OC, and JRA created the figures. LM wrote the first draft of the manuscript. OC, JRA, and JLW helped revise the drafted version before and after circulation to collaborators. All authors provided input on interpretation of results. All authors edited subsequent drafts of the manuscript. All authors read and approved the final version of the manuscript. All authors had access to all the data in the study and had final responsibility for the decision to submit for publication. LM and OC verified the data.

                Article
                NIHMS1698678
                10.1016/S2468-2667(21)00025-6
                8168455
                33765455
                7a539b5e-8107-434a-9013-396f09fdd0da

                This is an Open Access article under the CC BY-NC-ND 4.0 license. http://creativecommons.org/licenses/by/4.0/

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